Photos provided by Carolyn Forsyth

Artificial Intelligence is promising driverless cars and that has everyone excited. That kind of excitement usually means the hype is out there before anyone has thought about what this means for everyone who will be dealing with this revolution.

November, 2017

Rethinking the A.I. Revolution

I was exiting an Uber ride and asked the driver, “Say do you get many traffic tickets?” He replied that he received 2 to 3 per year.  That seemed reasonable when you consider he drives a lot, has to try to be efficient (a little over the speed limit) and may be exposed to more reckless or careless drivers than the average person.

The average ticket is about $150.00 and there aren’t statistics on the number of traffic tickets given out per city. It’s estimated that traffic ticket revenue for municipalities totals from $3.75 billion to $7.0 billion per year.  Again, that’s not supported by any statistical measures, as they don’t exist.

So what’s this got to do with Artificial Intelligence?

When we have access to driverless cars, there won’t be any traffic tickets. The Artificial Intelligence knows what the speed limit is, knows all the traffic rules and probably knows where the police like to watch for speeders. So, if there is no Human Intelligence driving the vehicle, and the vehicle always obeys the traffic rules, you don’t write many tickets. Removing that revenue from the cities and states (states control the highways) will result in some serious cash shortages for the cities. 

Let’s go back to Uber.  When Uber started, the company bypassed the existing rules on taxi cabs.  Generally, cities use a taxi medallion to limit the number of cabs on the streets. By restricting the number of cabs, the price for a trip was kept artificially higher than it would be if market forces were in play. New York City only allows licensed cabs to pick up fairs from a street side “hail.” Uber worked under a ride-sharing model. The innovation put them in direct competition with the taxi cab business as controlled and run by the municipalities and those who owned the cab medallions.

The net effect has been that cab drivers (who generally lease the rights to operate the cab from the medallion owners) found themselves in direct competition with Uber drivers who didn’t have to pay the medallion lease and medallion owners were now faced with the reality that the medallions weren’t as valuable anymore. Obviously there were legal fights but the new reality of Uber and ride-sharing was popular because it was cheaper to the customer, utilized a new technology (smart-phones) and the vehicles were cleaner and omni-present.

The other reality is that cities (and taxi drivers) want to control the number of “cabs” on the street. This keeps rates higher and made the medallions worth more to the buyers. City governments now found themselves with an item that would no longer generate revenues (or political donations).

Uber v Taxis.png

Artificial Intelligence for vehicles is going to present similar challenges. Imagine buses without drivers, delivery vehicles without drivers and passengers who are just that - passengers. Parking lots could conceivably be empty as workers are delivered to their workplace; the vehicle seeks out other commuters or goes to refuel. Again, the cities would be faced with a loss of parking revenue.

The cities are not prepared for this situation. The Uber model has broken the ability of the municipality to control the fares which should be determined by market forces. They may seek to tax that fare but it will not return the same amounts that were provided when they controlled the prices. Consumers react more readily to market forces. Additionally, the reduced need for drivers is going to have an economic impact for a significant number of workers which could impact both employment in the city and add to the cost for worker transitions to new employment.

Artificial Intelligence in vehicles is going to eventually arrive.  But the impact of that arrival has many unknowns and serious impacts on consumers, communities and government.